Stepan Stepanovic

Background

About Stepan Stepanovic

As a Maître-assistant at the University of Geneva, I apply my expertise in data science, cheminformatics, and computational chemistry to analyze trends in mass spectra (MS) for metabolomics and toxicology studies. With over 12 years of research experience in chemistry, computational methods, and data analytics, I have developed strong skills in machine learning, Linux, and various branches of chemistry, as well as mass spectrometry-based omics and life sciences in general. My research integrates cheminformatics, molecular modeling, and machine learning to decode MS data from CID, EAD, UVPD, and DMS techniques, uncovering key patterns in small molecule and peptide behavior. This approach reveals how molecular structures influence adduct formation, ion mobility, and fragmentation profiles across diverse MS settings, thereby enhancing the scope of multiomics studies. Beyond MS-based cheminformatics, I am involved in computational toxicology and catalysis projects. As for the teaching, I participate in Lab sessions for Bachelor-Analytical Chem course and give 4 lectures related to data analysis and machine learning to master students in their advanced Analytical Chem course. I have also developed and given an in-house python course for MSc and PhD students in our research group.